Scholar
Kenji Fukumizu
Google Scholar ID: Dav2k7cAAAAJ
The Institute of Statistical Mathematics
Machine learning
statistics
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Citations & Impact
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Citations
9,682
H-index
37
i10-index
91
Publications
20
Co-authors
26
list available
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Publications
14 items
Two-Sample Testing via Generative Processes
2026
Cited
0
Two-Sample Testing via Path-based Inference
2026
Cited
0
Domain-Adapted Diffusion Models for Conditional Independence Testing
2026
Cited
0
SynthDemo-RL: Breaking the Zero-Reward Barrier in VLA Adaptation with LLM-Guided Synthetic Demonstrations
2026
Cited
0
Accelerated Dynamic Importance Weighting with Versatile Divergence-Minimizing Estimators
2026
Cited
0
Provably Learning Diffusion Models under the Manifold Hypothesis: Collapse and Refine
2026
Cited
0
Flow Matching from Viewpoint of Proximal Operators
2026
Cited
0
Fast Flow Matching based Conditional Independence Tests for Causal Discovery
2026
Cited
0
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Background
Working on the theory and practice of machine learning from mathematical viewpoints
Research areas include deep learning, topological data analysis (TDA), and kernel methods
Deep learning research covers mathematical approaches such as equivariance, geometry, transfer learning, and generalization
Topological data analysis for analyzing complex geometrical objects
Kernel methods based on positive definite kernels and reproducing kernel Hilbert spaces for nonparametric data analysis
Co-authors
13 total
Arthur Gretton
Gatsby Computational Neuroscience Unit and Google Deepmind
Bharath Sriperumbudur
Pennsylvania State University
Bernhard Schölkopf
Director, Max Planck Institute for Intelligent Systems & ELLIS Institute Tübingen; Professor at ETH
Alex Smola
Boson AI
Dino Sejdinovic
Professor of Statistical Machine Learning, Adelaide University
Francis Bach
Inria - Ecole Normale Supérieure
Krikamol Muandet
CISPA - Helmholtz Center for Information Security
Motonobu Kanagawa
EURECOM